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Sentiment Classification of Newspaper Reviews using Neural Networks - Pandiaraj, A.
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  • Broschiertes Buch

The book "Sentiment Classification of Newspaper Reviews using Neural Networks" authored by A. Pandiaraj focuses on the application of neural network techniques in sentiment analysis of newspaper reviews. The book introduces the basic concepts of sentiment analysis, its importance in the field of natural language processing, and the different methods used for sentiment classification. The author then dives into the specifics of neural network-based sentiment analysis, covering topics such as pre-processing of data, feature extraction, and selection, as well as the design and implementation of…mehr

Produktbeschreibung
The book "Sentiment Classification of Newspaper Reviews using Neural Networks" authored by A. Pandiaraj focuses on the application of neural network techniques in sentiment analysis of newspaper reviews. The book introduces the basic concepts of sentiment analysis, its importance in the field of natural language processing, and the different methods used for sentiment classification. The author then dives into the specifics of neural network-based sentiment analysis, covering topics such as pre-processing of data, feature extraction, and selection, as well as the design and implementation of the neural network model. The book also discusses the challenges involved in sentiment classification, such as the handling of sarcasm and irony, and presents possible solutions. Readers will benefit from the practical examples and case studies included in the book, which demonstrate the application of neural network-based sentiment analysis on real-world datasets. Additionally, the author provides insights into the latest research trends in the field of sentiment analysis and discusses possible future directions. Overall, "Sentiment Classification of Newspaper Reviews using Neural Networks" is a valuable resource for researchers, practitioners, and students who are interested in the field of natural language processing, machine learning, and sentiment analysis.